Estimating Hepatitis C Virus Prevalence in US States and the District of Columbia, 2017-2020

Background State-level estimates of hepatitis C virus (HCV) prevalence are needed to guide resource allocation and to provide a baseline against which to measure progress toward elimination goals. Population prevalence is not directly observable, requiring estimation from indirect data sources. Methods We adapted a Bayesian spatial integrated abundance model to estimate state-level HCV prevalence during 2017-2020 across 48 states and the District of Columbia. The model integrated six HCV-related outcomes: acute and chronic surveillance cases, HCV-related deaths, observations of HCV in [MarketS

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